The present invention relates to a method for detection of defects on semiconductor wafers using a scanning electron microscope (SEM) and, more particularly, to a method for fast and reliable detection of defects by comparing a number of SEM images, each of which contains different information about the semiconductor device.
Defects on semiconductor wafers, such as particulate contamination, may render the wafers inoperative. Therefore, when manufacturing semiconductors, a quality inspection is usually performed to detect defects on the semiconductor wafers. Over the years, two main approaches--optical inspection and SEM inspection--have been developed and used to detect defects on semiconductor wafers.
Optical inspection of semiconductor wafers for defects detection is considered an effective and low cost method and is, therefore, the most widely used approach.
Various methods for detecting defects on semiconductor wafers using optical inspection equipment have been developed. For example, U.S. Pat. No. 4,805,123 to Specht et al., discloses a photomask and reticle inspection method and apparatus, wherein an examined surface area of a given image is compared with a corresponding reference area.
Also known are various methods for defect detection using SEM based equipment. For example, U.S. Pat. No. 4,794,646 to Jakeuchi et al. discloses an apparatus for detecting semiconductor wafer pattern defects wherein an inspected wafer area is compared to an image constructed from information, such as design rules, in a database.
As features on semiconductors become smaller than the wavelength of visible light, the size of defects which have to be detected falls below the resolution of conventional light optics. As a result, optical inspection systems become increasingly unreliable. Furthermore, even if the defect can be detected with optical systems, the resolution is such that it is impossible to extract accurate additional information, such as defect size and defect boundary. So the ability of optical systems to classify defects is highly limited.
Scanning electron microscopes (SEM) are capable of resolving features more than an order of magnitude smaller than the wavelength of visible light, and are, therefore, natural candidates for carrying out defect detection and classification on these scales. In order for an SEM-based semiconductor wafer defect detection method to be feasible for industrial purposes, the inspection must be fast and reliable and must generate as few false alarms as possible.
However, since speed requires images to be generated employing a large field of view, and since the faster electron microscope scanning is carried out, the poorer is the image contrast-to-noise ratio, defects covering small areas of the image are difficult to distinguish from pattern variations and noise, rendering fast scanning by existing SEM equipment, impractical due to the serious constraints on the image quality produced.
As mentioned, for speed purposes, it is required to generate images in a large field of view. This, in turn, means that defects covering only a small fraction of the semiconductor wafer image are obtained. Therefore, the image of any given defect carries relatively little information, typically insufficient for purposes of identifying and characterizing it with respect to the wafer pattern.
Rapidly acquired, large field of view, SEM image variations which are not associated with semiconductor wafer defects are well known. There is a legitimate pattern variation between two ideally identical semiconductor wafer areas, which, at SEM resolution, using the comparative approach described, may easily be interpreted as a defect. A second source of variations, not associated with semiconductor wafer defects, is variations characterizing the image formation process itself, such as noise or difference in focus. In both cases, the larger the variation, the higher the potential for false alarm.
The source of contrast in SEM images depends, to a large extent, on the energy range of the emitted electrons. For example, for backscattered electrons, contrast mostly reflects differences of material types. Although semiconductor wafers are made of a combination of materials, there is no guarantee that defects and wafer patterns are made of different materials. On the other hand, contrast produced by secondary electrons, emitted from the scanned object and having energy less than 50 eV, depends almost entirely on surface topography. This contrast is more suitable for semiconductor wafer defect detection.
The contrast-to-noise ratio for secondary electrons is inherently rather low but there are standard ways in which this ratio can be improved (see, for example, the book of L. Reimer, Image Formation in Low-Voltage Scanning Electron Microscopy, SPIE Optical Engineering Press, 1993).
One way to improve the contrast-to-noise ratio associated with secondary electrons is to use detectors devised to collect secondary electrons emitted from the wafer which are scattered in a limited angular sector, rather than collecting them all. Explicitly, edges scattering electrons in the direction of the detector will be brightened while edges facing away from the detector will be darkened. The effect of this shading is to greatly enhance image contrast. Secondary electron images formed from collecting secondary electrons in some limited angular sectors are referred to herein as `perspective images`. Detectors collecting secondary electrons of different angular sectors produce perspective images carrying different information about the wafer pattern.
Perspective imaging improves topographic contrast, but it does nothing to overcome the problems of the prior art described above of SEM scanning in a large field of view and comparing variation between images.
There is thus a widely recognized need for, and it would be highly advantageous to have, a fast and reliable method aimed at detecting defects in semiconductor wafers based on a comparison of perspective images and capable of filtering out large variations between compared images.